Systems and method for scanning subjects to ascertain body measurements

ABSTRACT

Systems and methods for performing body scans to ascertain body measurements of a subject. A radar based scanner may be used to generate a three dimensional image of a subject as a point cloud map of electromagnetic radiation reflected from a target region. The point cloud may be mapped to a parametric model of a standard human shape. The mapping may be optimized by adjusting parameters of the parametric model. The resulting parameters of the optimized model may be used to indicate the body measurements of the scanned subject

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/631,507 which was filed on Jan. 31, 2022 as a U.S. National PhaseApplication under 35 U.S.C. 371 of International Application No.PCT/IB62020/062121, which has an international filing date of Dec. 17,2020, which claims the benefit of priority from U.S. Provisional PatentApplication No. 62/948,825, filed Dec. 17, 2019, and U.S. ProvisionalPatent Application No. 62/955,482, filed Dec. 31, 2019, the contents ofwhich are incorporated by reference in their entirety.

FIELD AND BACKGROUND OF THE DISCLOSURE

The disclosure herein relates to systems and methods for performing bodyscans. In particular, the disclosure relates to using a radar scanner toascertain body measurements of a subject. The disclosure herein relatesto systems and methods for monitoring soap dispensers. In particular,the disclosure relates to the monitoring of level of contents of liquidsoap dispensers.

SUMMARY OF THE EMBODIMENTS

According to one aspect of the presently disclosed subject matter, asystem is introduced for scanning the body of a subject. The system maycomprise: a radar unit comprising, a preprocessor unit, and a processorunit. The radar unit may include at least one transmitter unit connectedto an oscillator and configured to transmit electromagnetic waves into amonitored region, and at least one receiver unit configured to receiveelectromagnetic waves reflected by objects within the monitored regionand operable to generate raw data. The preprocessor unit may beconfigured and operable to receive the raw data from the at least onereceiver unit and operable to generate filtered point cloud data. Theprocessor unit may have a memory unit, be configured to receive thefiltered point cloud data from the preprocessor, and operable to comparethe filtered point cloud with a human parametric model stored in amemory unit

Optionally, the preprocessor unit comprises an amplitude filter operableto generate filtered data by selecting from the raw data voxels havingamplitudes above a required threshold. Where appropriate, thepreprocessor unit comprises a voxel selector operable to further reducevoxel number in the filtered data thereby generating the point clouddata. Variously, the voxel selector is operable to sample the filtereddata and/or to cluster neighboring voxels. Accordingly, the amplitudemay be further operable to set the value of each voxel having anamplitude above the required threshold to ONE, and the value of eachvoxel having an amplitude below the required threshold to ZERO.

Where appropriate, the processor further comprises an optimizerconfigured and operable to compare positions of each voxel in the humanparametric model with positions of each voxel in the filtered pointcloud. Optionally, the processor further comprises a parameter selectorconfigured to receive comparison results from the optimizer and operableto generate a new candidate parametric model by adjusting parametersaccordingly.

Variously, the radar unit may be embedded behind a surface transparentto radio waves, such as in at least one of a group comprising: a wall, amirror frame, a window, under the floor, in a ceiling, an opticalmirror.

According to one aspect of the presently disclosed subject matter, amethod is taught for scanning the body of a subject. Such a method mayinclude: providing at least one radar unit comprising at least onetransmitter unit connected to an oscillator, and at least one receiverunit configured to receive electromagnetic waves; providing at least oneprocessor unit configured to generate a parametric model of the subject;storing at least one parametric human model in a memory unit;transmitting electromagnetic waves into a monitored region; receivingelectromagnetic waves reflected from objects in the monitored region;generating an amplitude matrix; generating a filtered point cloud; andcomparing the filtered point cloud with the parametric human model.

Where appropriate, the method further includes sending the amplitudematrix to a preprocessing unit.

Optionally, the step of generating filtered point cloud comprises:determining a required threshold amplitude; receiving raw data from thereceiver unit; and selecting raw data voxels having amplitudes above therequired threshold. Accordingly, the step of generating a filtered pointcloud may further comprise sampling filtered data and selecting voxels.Additionally or alternatively, the step of generating a filtered pointcloud further may comprise clustering neighboring voxels Whereappropriate, the step of generating a filtered point cloud furthercomprises setting the value of each voxel having an amplitude above therequired threshold to ONE, and setting the value of each voxel having anamplitude below the required threshold to ZERO.

Additionally or alternatively, the step of generating a filtered pointcloud may further comprise downsampling voxels and/or removing outlyingdata,

Where appropriate, optimizing parameters of the parameteric model of thesubject, for example by selecting initial parameters of for an initialmodel; comparing the filtered point cloud with the initial model; andadjusting parameters of the initial model accordingly.

BRIEF DESCRIPTION OF THE FIGURES

For a better understanding of the embodiments and to show how it may becarried into effect, reference will now be made, purely by way ofexample, to the accompanying drawings.

With specific reference now to the drawings in detail, it is stressedthat the particulars shown are by way of example and for purposes ofillustrative discussion of selected embodiments only, and are presentedin the cause of providing what is believed to be the most useful andreadily understood description of the principles and conceptual aspects.In this regard, no attempt is made to show structural details in moredetail than is necessary for a fundamental understanding; thedescription taken with the drawings making apparent to those skilled inthe art how the various selected embodiments may be put into practice.In the accompanying drawings:

FIG. 1 is a schematic block diagram indicating selected components of aradar based body scanning system of the disclosure;

FIGS. 2A-C schematically illustrate various possible radar scanningarrangement for use with the radar based body scanning system of thedisclosure;

FIG. 3 is a schematic illustration of a possible data flow within aradar based body scanning system of the disclosure;

FIG. 4 is a flow diagram illustrating a method for scanning body of asubject and ascertaining body measurement of a subject using a radarbased body scanning system of the disclosure;.

FIGS. 5A-C are schematic representations of an embodiment of a systemfor monitoring the level of a soap dispenser;

FIGS. 6A-C are a set of corresponding graphs indicating the transmittedand received wave signals for the monitoring system indicating differentcontent levels of the dispensers; and

FIG. 7 is a flowchart illustrating a possible method for monitoring soapdispensers.

DETAILED DESCRIPTION

Aspects of the present disclosure relate to systems and methods forperforming body scans to ascertain body measurements of a subject. Aradar based scanner may be used to generate a three dimensional image ofa subject as a point cloud map of electromagnetic radiation reflectedfrom a target region. The point cloud may be mapped to a parametricmodel of a standard human shape. The mapping may be optimized byadjusting parameters of the parametric model. The resulting parametersof the optimized model may be used to indicate the body measurements ofthe scanned subject.

Other aspects of the present disclosure relate to systems and methodsfor ascertaining size, shape and volume of inanimate objects, and inparticular to monitoring the content of a liquid in a vessel, eitherfrom within the vessel, or through electromagnetically penetrable wallsof a vessel. In particular, radar-based scanners may be used to monitorthe height level of the contents of liquid soap dispensers.

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely examples of the invention that may be embodied in various andalternative forms. The figures are not necessarily to scale; somefeatures may be exaggerated or minimized to show details of particularcomponents. Therefore, specific structural and functional detailsdisclosed herein are not to be interpreted as limiting, but merely as arepresentative basis for teaching one skilled in the art to variouslyemploy the present invention.

As appropriate, in various embodiments of the disclosure, one or moretasks as described herein may be performed by a data processor, such asa computing platform or distributed computing system for executing aplurality of instructions. Optionally, the data processor includes oraccesses a volatile memory for storing instructions, data or the like.Additionally or alternatively, the data processor may access anon-volatile storage, for example, a magnetic hard disk, flash-drive,removable media or the like, for storing instructions and/or data.

It is particularly noted that the systems and methods of the disclosureherein may not be limited in its application to the details ofconstruction and the arrangement of the components or methods set forthin the description or illustrated in the drawings and examples. Thesystems and methods of the disclosure may be capable of otherembodiments, or of being practiced and carried out in various ways andtechnologies.

Alternative methods and materials similar or equivalent to thosedescribed herein may be used in the practice or testing of embodimentsof the disclosure. Nevertheless, particular methods and materialsdescribed herein for illustrative purposes only. The materials, methods,and examples not intended to be necessarily limiting. Accordingly,various embodiments may omit, substitute, or add various procedures orcomponents as appropriate. For instance, the methods may be performed inan order different from described, and that various steps may be added,omitted or combined. In addition, aspects and components described withrespect to certain embodiments may be combined in various otherembodiments.

Referring now to FIG. 1 , a schematic block diagram indicates selectedcomponents of a radar based body scanning embodiment of the system 100B.The radar based body scanning system 100B includes a radar unit 1108,and a processor 120B.

The radar unit 1108 of the body scanning embodiment may be mounted to awall for example behind an optical mirror transparent to radio waves,embedded in the frame of a mirror, or the like where it may scan atarget region in front of the wall. The radar typically includes atleast one array of radio frequency transmitter antennas and at least onearray of radio frequency receiver antennas. The radio frequencytransmitter antennas are connected to an oscillator (radio frequencysignal source) and are configured and operable to transmitelectromagnetic waves towards the target region. The radio frequencyreceiver antennas are configured to receive electromagnetic wavesreflected back from objects within the target region.

The raw data generated by the receivers is typically a set of magnitudeand phase measurements corresponding to the waves scattered back fromthe objects in front of the array. Spatial reconstruction processing isapplied to the measurements to reconstruct the amplitude (scatteringstrength) at the three dimensional coordinates of interest within thetarget region. Thus each three dimensional section of the volume withinthe target region may represented by a voxel defined by four valuescorresponding to an x-coordinate, a y-coordinate, a z-coordinate, and anamplitude value.

Typically the receivers are connected to a pre-processing unit 114Bconfigured and operable to process the amplitude matrix of raw datagenerated by the receivers and produce a filtered point cloud suitablefor model optimization.

Accordingly, where appropriate, a preprocessing unit 114B may include anamplitude filter 116B operable to select voxels having amplitude above arequired threshold and a voxel selector 117B operable to reduce thenumber of voxels in the filtered data, for example by sampling the dataor clustering neighboring voxels. In this manner the filtered pointcloud may be output 118B to a processor 120B. It is further note thatthe filtered point cloud may further be simplified by setting theamplitude value of each voxel to ONE when the amplitude is above thethreshold and to ZERO when the amplitude is below the threshold.

The processor 120B which is in communication with the output 118B of thepreprocessor unit 114B is operable to receive the filtered point cloud124B from the output of the preprocessor 114B and to compare thefiltered point cloud with a human parametric model 125B stored in amemory unit.

The parametric model 125B may be generated by averaging scans ofmultiple subjects and/or applying machine learning to such scans andstored in the memory unit of the processor or remotely. The parametricmodel may be represented as a model function which receives a set ofvalues representing model parameters and returns as set of voxels whichmodel the subject.

By way of example, parameters may be selected from various measurablevalues of a subject, for example for a human subject parameters such asgender, height, weight, waist size, inner-thigh, inseam, arm-span, handspan, wrist to shoulder length, shoe size and the like as well ascombinations thereof may generate candidate models with characteristicvoxel sets. In some examples, separate parametric models may be providedfor male and female subjects.

Accordingly, the processor 120B may further include an optimizer 126Band a parameter selector 127B. The optimizer 126B may further beconfigured and operable to compare the positions of each voxel in theparametric model 125B with each voxel in the filtered point cloud 124B.The parameter selector 127B may be operable to receive the results ofthe comparison and to adjust the parameters accordingly so as generate anew candidate model. Once the optimizer 126B reaches an optimal modelwherein no further adjustment significantly improves the candidatemodel, that candidate model may be selected as the best fit model of thescanned subject.

The subject may itself be characterized by the measurements used asparameter values for generating the best fit model.

Variously, the scanning arrangement may be embedded in a wall, a mirrorframe, a window, under the floor, in a ceiling, behind an optical mirrortransparent to radio waves or the like as required.

Additionally or alternatively the scanning arrangement itself bedirected towards a mirror surface and may be configured and operable toextend the target region into the virtual reflected region inside themirror. Accordingly, shielded or eclipsed regions of the subject may berendered visible by reflection within the mirror.

Referring now to FIGS. 2A-C , various possible radar scanningarrangements may be used with the radar based body scanning system ofthe disclosure. In particular, with reference to FIG. 2A, the scanningarrangement may include a rectangular array of transmitter and receiverantennas. Such an arrangement may, for example, be incorporated into theframe of a mirror or the like. Accordingly, a subject may be scanned andmeasured while viewing themselves in the mirror. Further, as illustratedin FIG. 2B, the antennas may be embedded in a pseudorandomly scatteredarray of receivers and transmitters which may be networked andcontrolled centrally.

With reference now to FIG. 2C, another possible radar scanningarrangement for use with the radar based body scanning system of thedisclosure may include a set of nine radar scanning boards arranged in asquare of three rows and three columns Each radar scanning boards mayinclude a pair of linear array transmitter antennas and an orthogonallyorientated pair of linear array receiver antennas. Although eachscanning board may be controlled by dedicated controller chips andoscillators, these may be networked such that the set of scanning boardsoperate as a common unit generating a single set of raw amplitude datafor the target region.

Referring now to FIG. 3 , a schematic illustration is presented to showa possible data flow within the radar based body scanning system of thedisclosure. A subject 450 stands in a target region in front of a radarscanning arrangement 400 such as described herein. The scanningarrangement generates a set of raw data representing a three dimensionalamplitude map 402 indicating objects within the region including thesubject. The three dimensional amplitude matrix 402 may be filtered byremoving outlying voxels which are unconnected with the subject. Theclean map 404 may be further sampled to select only a subset of voxels406 such that a filtered amplitude map of the subject may be comparedwith a candidate parametric model 408. A candidate model 410 is thusconstructed which may then be optimized to generate the best fit model412.

Referring now to FIG. 4 is a flow diagram illustrating a method forscanning body of a subject and ascertaining body measurement of asubject using a radar based body scanning system of the disclosure.

The method incudes, providing a scanning radar 1002, providing aprocessing unit 1004, and providing a parametric human model 1006.

The scanning arrangement may scan a subject may be in the target regionin front of the array 1008, thereby generating amplitude data for theregion 1010.

The amplitude matrix is sent to a preprocessing unit 1012, whichgenerates a filtered point cloud 1014. Optionally, the data may beprocessed by removing data below a threshold amplitude value 1016,removing outlying data 1018 and downsampling voxels 1020.

The resulting point cloud may be sent to a processor where a model isoptimized 1022 for example by selecting a candidate set of parameters1024, comparing the point cloud with the candidate model 1026, adjustingparameters 1028 and repeating until no further improvements are made.

It is particularly note that the output of the scanning device is athree dimensional point cloud. However, some of the regions of the pointcloud may be missing from the scan for example due to shielding effectsor regions at angles with poor coverage. Various compensation techniquesmay be used to interpolate for the missing data such as local averagingor the like.

Various optimization processes may be used for example, defining anobjective function, comparing the candidate parametric model with thescanned point cloud, identifying which voxels in the candidateparametric model are geometrically closest to corresponding points inthe point cloud, and calculating the Euclidean distance Δ between thesepoints as given by:

Δ=√{square root over ((x-x_(m))²+(y-y_(m))²+(z-z_(m))²)}

where x is the x-coordinate of the point in the point cloud, x_(m) isthe x-coordinate of the closest point in the candidate parametric model,y is the y-coordinate of the point in the point cloud, y_(m) is they-coordinate of the closest point in the candidate parametric model, zis the z-coordinate of the point in the point cloud, and z_(m) is thez-coordinate of the closest point in the candidate parametric model.

The value of the sum of all the Euclidean distances ΣΔ_(i) may beminimized by various optimization algorithms, such as Sequential LeastSquares Quadratic Programming (SLSQP) for example. In this way theoptimal parameters may be selected for the human parametric model. Otheroptimization methods will occur to those skilled in the art.

The generated best fit model may be used to find full body measurementseven from missing parts in the scan and potentially of body parts thathaven't been scanned at all.

Well stocked soap dispensers are essential to the sanitation of publicservices. However, ensuring that the soap dispensers do not run outrequires frequent inspection of dispensers which often difficult toaccess. Such inspection is time consuming, costly and labor intensive.There is, therefore, for a need for a cost effective system and methodfor automating the monitoring of contents of soap dispensers.

Referring now to FIG. 5A, a schematic representation is shown of anembodiment of a system for monitoring the level of a liquid in a soapdispenser 500.

The soap dispenser 500 of the example includes a soap reservoir 510 anda dispensing nozzle 520. Other soap dispensers will occur to thoseskilled in the art. It is a particular feature of such soap dispensersthat the reservoir includes a container for containing a volume of soapthe height of the soap contents indicates the volume of soap remainingin the reservoir.

Typically the height of the soap has been periodically inspectedmanually to ascertain the contents of the soap dispenser and to decidewhether the soap needs to be replaced or replenished.

In order to automate the contents inspection, the soap reservoir of theinvention includes a monitoring system configured and operable tomonitor the level of the soap reservoir. The monitoring system maycomprise a radar chip including a transmitter, a receiver, a controllerand an output mechanism.

The transmitter may include an oscillator connected to at least onetransmitter antenna or an array of transmitter antennas and configuredto produce a beam of electromagnetic radiation, such as microwaveradiation or the like, directed towards the surface of the soapreservoir.

The receiver may include at least one receiving antenna or array ofreceiver antennas configured and operable to receive electromagneticradiation. Typically a processor is provided to identify reflectedradiation received by the receiver which having the characteristicfrequency of the transmitted beam. It is a particular feature of thecurrent disclosure that the receiver further includes a timer for timingreceived signals.

Accordingly, radiation directed towards the surface of the soapreservoir may be reflected back from the surface and received by thereceiver. Because electromagnetic radiation travels at a fixed speed,the distance from the monitor to the surface of the soap reservoir maybe calculated by measuring the time taken for a transmitted beam to bereceived back by the receiver.

Referring to the graph of FIG. 6A, a corresponding graph is presentingindicating the transmitted and received wave signals for the monitoringsystem indicating a well stocked soap dispenser.

It is noted that there is a measurable time interval Δt between thetransmitted signal TX and the received signal RX. The volume V of thesoap reservoir relates to the time interval according to the formula:

V=A(H-cΔt)

where A is the area of the base of the reservoir, H is the height fromthe base of the reservoir to the monitor antennas and c is the speed oftransmitted radiation (typically the speed of electromagnetic radiationthrough air).

Accordingly, the longer the time interval Δt the lower the level of thesoap.

Referring now to FIG. 5B, a soap dispenser is schematically representedin which the level is lower than in FIG. 5A. Such a soap dispenser maynot require immediate replenishment. FIG. 6B shows the correspondingresponse graph for the monitor in which the time interval Δt is longerthan in FIG. 6A indicating that the soap level is reduced.

Referring now to FIG. 5C, another soap dispenser is schematicallyrepresented in which the level has dropped below a threshold requiringreplenishment. FIG. 6C shows the corresponding response graph for themonitor in which the time interval Δt is longer than the threshold timeinterval Δt_(th) thereby indicating that the soap will need to bereplenished.

Reference is now made to the flowchart of FIG. 7 which illustrates apossible method for monitoring soap dispensers.

The transmitter transmits radiation in the general direction of thesurface of the soap reservoir. As the signal is transmitted a timer isstarted.

A reflected signal is received by the receiver antenna. As soon as thereflected signal is received, the timer is stopped.

The controller or processor may then compare the measured time intervalΔt with the threshold time interval Δt_(th). Where the measured timeinterval Δt is shorter than the threshold time interval Δt_(th) thesystem may repeat the first steps. Where the measured time interval Δtexceeds the threshold time interval Δt_(th) the system may register alow soap level event.

The radar can be located outside the container and inspect the level ofthe soap through a dielectric wall or cover. By this the chances thatthe radar components are stained by soap is reduced.

Another embodiment of the invention comprises an imaging radar, such asMIMO radar comprising multiple transmit and receive antennas so as toobtain spatial resolution. Such radar can observe the soap containerfrom the side, being completely outside the container. The method takesadvantage from the fact that soap containers are typically made ofdielectric material, such as plastic, glass or ceramics. Thereflectivity of the wall which is in contact with the soap (or otherliquid, for that purpose) is different from the reflectivity of the wallwhich is backed by air (above the level of the liquid). By producing animage of reflectivity versus height, the level of soap can be detected.The volume of the liquid may be further estimated using a parametricmodel of the container an its cross-section.

Various actions may be triggered by the low soap level event, such asturning on a warning light, a warning signal or the like. Further, wherethe system includes a communication unit, the unit may be operable tosend an alert, notify a third party for example a caretaker, orderly,janitor, sanitary officer or the like such that appropriate action maybe taken. Still other alert responses may occur to those skilled in theart.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the disclosure, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable sub-combination or as suitable in any other describedembodiment of the disclosure. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that other alternatives,modifications, variations and equivalents will be apparent to thoseskilled in the art. Accordingly, it is intended to embrace all suchalternatives, modifications, variations and equivalents that fall withinthe spirit of the invention and the broad scope of the appended claims.Additionally, the various embodiments set forth hereinabove aredescribed in terms of exemplary block diagrams, flow charts and otherillustrations. As will be apparent to those of ordinary skill in theart, the illustrated embodiments and their various alternatives may beimplemented without confinement to the illustrated examples. Forexample, a block diagram and the accompanying description should not beconstrued as mandating a particular architecture, layout orconfiguration.

Technical Notes

Technical and scientific terms used herein should have the same meaningas commonly understood by one of ordinary skill in the art to which thedisclosure pertains. Nevertheless, it is expected that during the lifeof a patent maturing from this application many relevant systems andmethods will be developed. Accordingly, the scope of the terms such ascomputing unit, network, display, memory, server and the like areintended to include all such new technologies a priori.

As used herein the term “about” refers to at least ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to” and indicatethat the components listed are included, but not generally to theexclusion of other components. Such terms encompass the terms“consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” may include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the disclosure may include a plurality of “optional”features unless such features conflict.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween. It should be understood,therefore, that the description in range format is merely forconvenience and brevity and should not be construed as an inflexiblelimitation on the scope of the disclosure. Accordingly, the descriptionof a range should be considered to have specifically disclosed all thepossible sub-ranges as well as individual numerical values within thatrange. For example, description of a range such as from 1 to 6 should beconsidered to have specifically disclosed sub-ranges such as from 1 to3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc.,as well as individual numbers within that range, for example, 1, 2, 3,4, 5, and 6 as well as non-integral intermediate values. This appliesregardless of the breadth of the range.

It is appreciated that certain features of the disclosure, which are,for clarity, described in the context of separate embodiments, may alsobe provided in combination in a single embodiment. Conversely, variousfeatures of the disclosure, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable sub-combination or as suitable in any other describedembodiment of the disclosure. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments unless the embodiment is inoperative without thoseelements.

Although the disclosure has been described in conjunction with specificembodiments thereof, it is evident that many alternatives, modificationsand variations will be apparent to those skilled in the art.Accordingly, it is intended to embrace all such alternatives,modifications and variations that fall within the spirit and broad scopeof the appended claims.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present disclosure. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

The scope of the disclosed subject matter is defined by the appendedclaims and includes both combinations and sub combinations of thevarious features described hereinabove as well as variations andmodifications thereof, which would occur to persons skilled in the artupon reading the foregoing description.

What is claimed is:
 1. A system for scanning the body of a subject, thesystem comprising: a radar unit comprising: at least one transmitterunit connected to an oscillator and configured to transmitelectromagnetic waves into a monitored region, and at least one receiverunit configured to receive electromagnetic waves reflected by objectswithin the monitored region and operable to generate raw data; apreprocessor unit configured and operable to receive the raw data fromthe at least one receiver unit and operable to reduce number of voxel ofdata and thereby to generate filtered point cloud data; a processor unithaving a memory unit and configured to receive the filtered point clouddata from the preprocessor unit and operable to compare the filteredpoint cloud with a human parametric model stored in a memory unit. 2.The system of claim 1 wherein the preprocessor unit comprises anamplitude filter operable to generate filtered data by selecting fromthe raw data voxels having amplitudes above a required threshold.
 3. Thesystem of claim 2 wherein the preprocessor unit comprises a voxelselector operable to further reduce voxel number in the filtered datathereby generating the point cloud data.
 4. The system of claim 2wherein the voxel selector is operable to sample the filtered data. 5.The system of claim 2 wherein the voxel selector is operable to clusterneighboring voxels.
 6. The system of claim 2 wherein the amplitudefilter is further operable to set the value of each voxel having anamplitude above the required threshold to one, and the value of eachvoxel having an amplitude below the required threshold to zero.
 7. Thesystem of claim 1 wherein the processor further comprises an optimizerconfigured and operable to compare positions of each point in the humanparametric model with positions of each voxel in the filtered pointcloud.
 8. The system of claim 7 wherein the processor further comprisesa parameter selector configured to receive comparison results from theoptimizer and operable to generate a new candidate parametric model byadjusting parameters of the human parametric model accordingly.
 9. Thesystem of claim 1 wherein the radar unit is embedded behind a surfacetransparent to radio waves.
 10. The system of claim 1 wherein the radarunit is embedded in at least one of a group comprising: a wall, a mirrorframe, a window, under the floor, in a ceiling, an optical mirror.
 11. Amethod for scanning the body of a subject comprising: providing at leastone radar unit comprising at least one transmitter unit connected to anoscillator, and at least one receiver unit configured to receiveelectromagnetic waves; providing at least one processor unit configuredto generate at least one human parametric model of the subject; storingthe at least one human parametric model in a memory unit; transmittingelectromagnetic waves into a monitored region; receiving electromagneticwaves reflected from objects in the monitored region; generating anamplitude matrix of raw data generated by the receivers; processing theamplitude matrix and generating a filtered point cloud; and comparingthe filtered point cloud with the at least one human parametric humanmodel.
 12. The method of claim 11 further comprising sending theamplitude matrix to a preprocessing unit.
 13. The method of claim 11wherein the step of generating filtered point cloud comprises:determining a required threshold amplitude; receiving raw data from thereceiver unit; and selecting raw data voxels having amplitudes above therequired threshold.
 14. The method of claim 13 wherein the step ofgenerating a filtered point cloud further comprises sampling filtereddata and selecting voxels.
 15. The method of claim 13 wherein the stepof generating a filtered point cloud further comprises clusteringneighboring voxels.
 16. The method of claim 13 wherein the step ofgenerating a filtered point cloud further comprises setting the value ofeach voxel having an amplitude above the required threshold to one, andsetting the value of each voxel having an amplitude below the requiredthreshold to zero.
 17. The method of claim 11 wherein the step ofgenerating a filtered point cloud further comprises downsampling voxels.18. The method of claim 11 wherein the step of generating a filteredpoint cloud further comprises removing outlying data.
 19. The method ofclaim 11 further comprising optimizing parameters of the at least onehuman parametric model of the subject.
 20. The method of claim 19wherein the step of optimizing the parameters of the parametric model ofthe subject comprises: selecting initial parameters of an initial model;comparing the filtered point cloud with the initial model; and adjustingthe initial parameters of the initial model accordingly.